What Relevant Immune Monitoring and Correlative Study Criteria Do We Use?

Transcription

1 What Relevant Immune Monitoring and Correlative Study Criteria Do We Use? Lisa H. Butterfield, Ph.D. Associate Professor of Medicine, Surgery and Immunology University of Pittsburgh Cancer Institute Director, UPCI Immunologic Monitoring and Cellular Products Laboratory

2 Disclosure The following relationships exist related to this presentation: Lisa H. Butterfield, None Ph.D. The following relationships exist: Advisory Board participant: EMD Serono, Novartis, Ziopharm Special Advisor: Kite Pharma

3 Correlations between Immune Monitoring and Clinical Outcome Vaccination of vulvar intraepithelial neoplasia patients with long peptides from HPV16 {Welters 10}. Investigators tested lymphocyte proliferation and cytokine production to immunizing antigens as well as circulating regulatory T cells (Treg). Their study showed that the patients with the strongest proliferation, positive IFNγ and IL-5 production, and lowest Treg were those with complete responses (CR) to therapy. A trial testing WT-1 antigen in AML patients indentified significant changes in WT-1 specific CD8 + T cell frequencies, and more dramatic activation of circulating NK cells in patients with CRs {Van Tendeloo 10}. A recent study testing a multi-peptide vaccine in renal cancer patients demonstrated that inhibition of Treg strengthened antitumor immunity, frequencies of specific subsets of MDSC at baseline were critical, and that improved clinical outcome correlated with a larger number of peptides responded to {Walter 12 }. This last observation has been made in previous multi-peptide vaccine trials {Banchereau, 01}. In patients treated with ipilimumab, a number of groups have examined humoral and cellular responses from peripheral blood. Recently, integrated humoral and CD8 + T cell response to the shared, immunogenic cancer/testes antigen NY-ESO-1 was shown to be a significant immunologic measure correlating with clinical outcomes {Yuan 11}. In a related publication, circulating T cells specific to NY-ESO-1 and MART- 1 antigens (but not MAGE-A3 or survivin antigens) were correlated with melanoma patient survival {Weide 12}. A final example of an immune measure that several independent groups have correlated to clinical outcome is epitope spreading or determinant spreading. This acquisition of T cell and antibody reactivity to shared antigens or epitopes other than those used in a vaccine, has been observed in melanoma {Ranieri 00; Butterfield, 03; Ribas 04; Butterfield 08}, renal cancer {Wierecky 06 } and breast cancer {Disis 02 }.

4 Correlations between Immune Monitoring and Clinical Outcome Vaccination of vulvar intraepithelial neoplasia patients with long peptides from HPV16 {Welters 10}. Investigators tested lymphocyte proliferation and cytokine production to immunizing antigens as well as circulating regulatory T cells (Treg). Their study showed that the patients with the strongest proliferation, positive IFNγ and IL-5 production, and lowest Treg were those with complete responses (CR) to therapy. A trial testing WT-1 antigen in AML patients indentified significant changes in WT-1 specific CD8 + T cell frequencies, and more dramatic activation of circulating NK cells in patients with CRs {Van Tendeloo 10}. A recent study testing a multi-peptide vaccine in renal cancer patients demonstrated that inhibition of Treg strengthened antitumor immunity, frequencies of specific subsets of MDSC at baseline were critical, and that improved clinical outcome correlated with a larger number of peptides responded to {Walter 12 }. This last observation has been made in previous multi-peptide vaccine trials {Banchereau, 01}. In patients treated with ipilimumab, a number of groups have examined humoral and cellular responses from peripheral blood. Recently, integrated humoral and CD8 + T cell response to the shared, immunogenic cancer/testes antigen NY-ESO-1 was shown to be a significant immunologic measure correlating with clinical outcomes {Yuan 11}. In a related publication, circulating T cells specific to NY-ESO-1 and MART- 1 antigens (but not MAGE-A3 or survivin antigens) were correlated with melanoma patient survival {Weide 12}. A final example of an immune measure that several independent groups have correlated to clinical outcome is epitope spreading or determinant spreading. This acquisition of T cell and antibody reactivity to shared antigens or epitopes other than those used in a vaccine, has been observed in melanoma {Ranieri 00; Butterfield, 03; Ribas 04; Butterfield 08}, renal cancer {Wierecky 06 } and breast cancer {Disis 02 }.

5 Correlations between Immune Monitoring and Clinical Outcome Vaccination of vulvar intraepithelial neoplasia patients with long peptides from HPV16 {Welters 10}. Investigators tested lymphocyte proliferation and cytokine production to immunizing antigens as well as circulating regulatory T cells (Treg). Their study showed that the patients with the strongest proliferation, positive IFNγ and IL-5 production, and lowest Treg were those with complete responses (CR) to therapy. A trial testing WT-1 antigen in AML patients indentified significant changes in WT-1 specific CD8 + T cell frequencies, and more dramatic activation of circulating NK cells in patients with CRs {Van Tendeloo 10}. A recent study testing a multi-peptide vaccine in renal cancer patients demonstrated that inhibition of Treg strengthened antitumor immunity, frequencies of specific subsets of MDSC at baseline were critical, and that improved clinical outcome correlated with a larger number of peptides responded to {Walter 12 }. This last observation has been made in previous multi-peptide vaccine trials {Banchereau, 01}. In patients treated with ipilimumab, a number of groups have examined humoral and cellular responses from peripheral blood. Recently, integrated humoral and CD8 + T cell response to the shared, immunogenic cancer/testes antigen NY-ESO-1 was shown to be a significant immunologic measure correlating with clinical outcomes {Yuan 11}. In a related publication, circulating T cells specific to NY-ESO-1 and MART- 1 antigens (but not MAGE-A3 or survivin antigens) were correlated with melanoma patient survival {Weide 12}. A final example of an immune measure that several independent groups have correlated to clinical outcome is epitope spreading or determinant spreading. This acquisition of T cell and antibody reactivity to shared antigens or epitopes other than those used in a vaccine, has been observed in melanoma {Ranieri 00; Butterfield, 03; Ribas 04; Butterfield 08}, renal cancer {Wierecky 06 } and breast cancer {Disis 02 }.

6 Correlations between Immune Monitoring and Clinical Outcome Vaccination of vulvar intraepithelial neoplasia patients with long peptides from HPV16 {Welters 10}. Investigators tested lymphocyte proliferation and cytokine production to immunizing antigens as well as circulating regulatory T cells (Treg). Their study showed that the patients with the strongest proliferation, positive IFNγ and IL-5 production, and lowest Treg were those with complete responses (CR) to therapy. A trial testing WT-1 antigen in AML patients indentified significant changes in WT-1 specific CD8 + T cell frequencies, and more dramatic activation of circulating NK cells in patients with CRs {Van Tendeloo 10}. A recent study testing a multi-peptide vaccine in renal cancer patients demonstrated that inhibition of Treg strengthened antitumor immunity, frequencies of specific subsets of MDSC at baseline were critical, and that improved clinical outcome correlated with a larger number of peptides responded to {Walter 12 }. This last observation has been made in previous multi-peptide vaccine trials {Banchereau, 01}. In patients treated with ipilimumab, a number of groups have examined humoral and cellular responses from peripheral blood. Recently, integrated humoral and CD8 + T cell response to the shared, immunogenic cancer/testes antigen NY-ESO-1 was shown to be a significant immunologic measure correlating with clinical outcomes {Yuan 11}. In a related publication, circulating T cells specific to NY-ESO-1 and MART- 1 antigens (but not MAGE-A3 or survivin antigens) were correlated with melanoma patient survival {Weide 12}. A final example of an immune measure that several independent groups have correlated to clinical outcome is epitope spreading or determinant spreading. This acquisition of T cell and antibody reactivity to shared antigens or epitopes other than those used in a vaccine, has been observed in melanoma {Ranieri 00; Butterfield, 03; Ribas 04; Butterfield 08}, renal cancer {Wierecky 06 } and breast cancer {Disis 02 }.

7 Immunologic Biomarkers in Cancer Participating Organizations: Association for Immunotherapy of Cancer (CIMT) Biotherapy Development Association (BDA) Cancer Vaccine Consortium (CVC) of the Cancer Research Institute (CRI) Food and Drug Administration (FDA) Italian Network for Tumor Biotherapy (NIBIT) Japanese Society of Cancer Immunology (JSCI) National Cancer Institute (NCI) National Institutes of Health (NIH) Nordic Center for Development of Antitumour Vaccines (NCV-network)

8 May 2011 Variability: 1. Patient 2. Blood draw 3. Processing/cryo/thaw 4. Cellular product 5. Assay choice 6. Assay conduct 7. Assay analysis 8. Data reporting 9. Next cool new assay Recommendations: 1. Save DNA/RNA/cells/tumor; include healthy donor control 2. Standardized procedures 3. Standardized procedures 4. Functional assays to characterize/develop potency 5. Standardized, functional 6. SOP 7. Appropriate biostatistical methods 8. Full details, controls, QA 9. Sufficient blood/tissue to interrogate the samples now, as well as later, to generate new hypotheses.

9 ImmunoAssay Proficiency Panel Program The program s objectives are: 1)to offer an external validation program, and 2)to enhance assay harmonization. The Proficiency Panel Program seeks to identify: issues and deficiencies of current assay practices; sources for assay variability within and among institutions; protocol details that optimize assay performance. Define criteria for and support harmonization & validation of the assay for individual member laboratories. Determine the value of resulting criteria in the cancer immunotherapy community. Offer training programs to the cancer immunotherapy community to enhance assay performance and comparability between laboratories. Establish immune assays as standard monitoring tools, if feasible. ELISPOT -- Dr. Sylvia Janetzki, ZellNet Consulting ICS -- Dr. Lisa McNeil, Wyeth Multimer (Tetramer/Pentamer) Staining -- Dr. Pedro Romero, Ludwig Institute for Cancer Research, Lausanne, Switzerland, and Dr. Cedrik Britten, University of Leiden, The Netherlands Luminex Dr. Michael Kalos, Univ. Pennsylvania Central laboratory services, cells, and shipping are provided by the Immunology Quality Assurance Center (IQAC) of the Duke Human Vaccine Institute under the leadership of Dr. Thomas Denny.

10 Immunity 37, July 27, 2012 T Cell Assays and MIATA: The Essential Minimum for Maximum Impact C.M. Britten,1,* S. Janetzki,2 L.H. Butterfield,3 G. Ferrari,4 C. Gouttefangeas,5 C. Huber,6 M. Kalos,7 H.I. Levitsky,8 H.T. Maecker,9 C.J.M. Melief,10 J. O Donnell-Tormey,11 K. Odunsi,12 L.J. Old,13 T.H.M. Ottenhoff,14 C. Ottensmeier,15 G. Pawelec,16 M. Roederer,17 B.O. Roep,18 P. Romero,19 S.H. van der Burg,20 S. Walter,21 A. Hoos,22 and M.M. Davis23 Lack of conformity on reporting data hampers the ability to objectively evaluate data. Minimal Information About T cell Assays ( MIATA ): we propose to generate recommendations on the minimum information required to allow an objective and thorough interpretation of published results from immunological T cell assays. Any recommendation in the proposed Modules is strictly based on supporting published data. Long-term goal of MIATA: adapt the reporting framework for annotations of immune monitoring data sets from human studies for a central database, possibly in the context of a Human Immunity Project. This may include structured database vocabulary.

11 May 2011 Putting the recommendations into practice:

12 Multi-Antigen-AdV-Transduced DC with IFN Boost Trial DIAGRAM IFN boost 3 tumor antigen Adenovirus SCHEDULE leukapheresis DC 3 vaccines, intra-dermal, 10 7 DC per injection, every other week Leukapheresis/Biopsy: CD8+/CD4+ PBMC: -Multi-cytokine ELISPOT for immunizing antigens -Determinant Spreading ELISPOT -Serum Luminex -Tetramer Assay/phenotyping -Avidity (A2/DR4) -NK activation -TIL analyses -Tumor antigen analysis Randomize 50% to AdV/DC AdV/DC AdV/DC Leuk. #1 #1 #2 #3 Leuk. #2 IFN Leuk. #3 30 Patients Randomized: 1:1 to high dose i.v. IFN Tumor Biopsy: Analysis of vaccine antigens (not inclusion criterion) Analysis of additional antigens (for potential determinant spreading assay antigens) day 14 day 0 day +14 day +28 day +42 day +56 (for 4 weeks) 14 days post IFN VECTOR MAP CMV-Tyrosinase-IRES-MART-1-SV40pA E1 AdV type 5 RSV-MAGEA6-BGHpA E3

13 Immune Response, Clinical Response and Determinant Spreading Immune response to the vaccine-encoded antigens can correlate with clinical response, but the magnitude of CD8+ T cells to a specific immunizing peptide rarely defines the clinical responders. Total immune score, breadth of immunity and determinant spreading may be more critical. How to strengthen and broaden immunity: 1. Multiple CD8/class I epitopes (dominant and subdominant) 2. Include cognate CD4 helper stimulation 3. Further improve the DC (subtype, maturation) 4. Promote innate immunity (NK cells) 5. Immunize with multiple antigens 6. Boost the immune response (cytokines)

14 In Vivo Cross-Presentation A recent study testing a multi-peptide vaccine in renal cancer patients demonstrated improved clinical outcome correlated with a larger number of peptides responded to {Walter 12 }. This last observation has been made in previous multi-peptide vaccine trials {Banchereau, 01}. Recently, integrated humoral and CD8 + T cell response to the shared, immunogenic cancer/testes antigen NY-ESO-1 was shown to be a significant immunologic measure correlating with clinical outcomes {Yuan 11}. Several independent groups have correlated to clinical outcome is epitope spreading or determinant spreading. This acquisition of T cell and antibody reactivity to shared antigens or epitopes other than those used in a vaccine, has been observed in melanoma {Ranieri 00; Butterfield, 03; Ribas 04; Butterfield 08}, renal cancer {Wierecky 06 } and breast cancer {Disis 02 }. Immunologic biomarkers as correlates of clinical response to cancer immunotherapy. There is a need to identify immune biomarkers capable of predicting clinical response Biomarkers that measure the magnitude of the Type I immune response generated with immune therapy, epitope spreading, and autoimmunity are readily detected in the peripheral blood and, in clinical trials of cancer immunotherapy, have been associated with response to treatment. {Disis, CII, 11}.

15 In Vivo Cross-Presentation Immunologic biomarkers as correlates of clinical response to cancer immunotherapy. There is a need to identify immune biomarkers capable of predicting clinical response Biomarkers that measure the magnitude of the Type I immune response generated with immune therapy, epitope spreading, and autoimmunity are readily detected in the peripheral blood and, in clinical trials of cancer immunotherapy, have been associated with response to treatment. {Disis, CII, 11}. How should this be assessed? T cells infiltrating the tumor (antigen source)? Inflammed tumor (mrna/protein)? Broad antigen recognition (many CD8+ T cell clones activated)? Functional cellular + humoral immunity induced? Reduced immune suppression? Tumor private/mutated antigen responses?

16 tumor Blood Digested tumor/til cell suspension Direct whole blood assays PBMC Tumor section IHC Tumor and lymphocytes serum plasma PBMC Freshly tested or cryopreserved for batch testing obtain absolute counts and percentages lymphs TESTING: Total lymphocyte subsets Antigen-specific T cells (CD4+, CD8+) Antigen-specific antibodies NK cells Myeloid DC Plasmacytoid DC Cytokine/chemokines/ growth factors Treg MDSC Frequency, phenotype, function, activation, suppression, expression of key molecules genetic polymorphisms RNA expression monos Leukapheresis Elutriation

17 AdVTMM2/DC +/- IFNα clinical trial (30 pt.) a. Clinical outcomes in stage IV patients b. Immunologic outcomes (blood and TIL; post-vaccine and post-ifnα) i. CD8+ T cells specific for vaccine antigens ii.cd4+ T cells specific for vaccine antigens iii. NK cell activation (flow), infiltration (TIL flow, IHC) iv. T cell response to spreading antigens: gp100, NY-ESO-1, etc. v. T and NK cell responses to autologous tumor (blood and TIL) vi. Antibody responses to melanoma antigens vii. Treg and MDSC regulatory status c. AdV responses i. CD4+ hexon T cells (frequency, skewing) ii. CD4+ and CD8+ T cells to the total viral proteins iii. Anti-AdV total antibodies (ELISA) iv. Anti-AdV neutralizing antibodies (flow)

18 AdVTMM2/DC +/- IFNα clinical trial primary immune endpoint a. Clinical outcomes in stage IV patients b. Immunologic outcomes (blood and TIL; post-vaccine and post-ifnα) i. CD8+ T cells specific for vaccine antigens ii.cd4+ T cells specific for vaccine antigens iii. NK cell activation (flow), infiltration (TIL flow, IHC) iv. T cell response to spreading antigens: gp100, NY-ESO-1, etc v. T and NK cell responses to autologous tumor (blood and TIL) vi. Antibody responses to melanoma antigens vii. Treg and MDSC regulatory status c. AdV responses i. CD4+ hexon T cells (frequency, skewing) ii. CD4+ and CD8+ T cells to the total viral proteins iii. Anti-AdV total antibodies (ELISA) iv. Anti-AdV neutralizing antibodies (flow) exploratory hypothesis-generating

19 Exploratory can be important MDSC Reduced MDSC correlates with better outcome Treg Treg increasing in the more effective immunotherapy trial Forest plot of the multicolor flow cytometry data comparing T-reg and MDSC on PBMC at baseline and following treatment (day 29 and day 85) in patients treated with tremelimumab and interferon-α. Tarhini AA, J Immunother., 2012.

20 Mechanism of Response and Biomarkers of Response from the AdVTMM2/DC +/- IFNα clinical trial tumor d. Vaccine Transcriptional Profiling (+/- AdVTMM2) Compare to standard DC vaccine pheno/cytokine/ag expression e. Tumor Transcriptional Profiling (pre, post DC, post IFN) How are tumors modulated by DC and IFNa therapy? Baseline tumor profile? f. Peripheral blood signaling g. Serum profiling (autoimmunity antibodies, LDH, CRP) Support previously identified serum biomarkers/autoimmunity? h. Molecular mimicry with mycoplasma i. Germline DNA SNP analysis DC

21 Immune Score Tumor anatomy showing the features of the immune contexture. J. Galon, W. Fridman; Science, The Immune Score as a New Possible Approach for the Classification of Cancer Jérôme Galon1,2,3,4,5*, Franck Pagès1,2,3,4, Francesco M Marincola5,6, Magdalena Thurin7, Giorgio Trinchieri8, Bernard A Fox5,9,10, Thomas F Gajewski5,11 and Paolo A Ascierto12,13 Journal of Translational Medicine 2012

22 Immunologic Monitoring and Cellular Products Laboratory The Cellular Products Laboratory (CPL) is dedicated to preparation of products for tumor vaccines and for cellular and gene therapy of cancer. vaccine preparation sterility and safety evaluations of generated products assists in the preparation of INDs operates according to FDA criteria for current good manufacturing practice (cgmp). The Immunologic Monitoring Laboratory (IML) is responsible for serial monitoring of immunologic functions in patients with cancer. state-of-the-art immunologic assays rigorous quality control program development of new assays advice on test selection and result interpretation The Tissue Procurement Facility (TPF) provides tissue and blood banking support under current Good Tissue Practice (cgtp) criteria. CLIA certified; inspected by CAP and the state of PA; registered with FDA ( ) FDA Master file: BB-MF-12244; FACT accredited

23 Services Specimen intake, processing, banking Cell bank preparation Culture of peptide-specific T cells Culture of tumor infiltrating lymphocytes (TIL) DC preparation (peripheral blood, stem cells) Gene transfer: any human cells Expansion of stem cells Vaccine production for intra-tumor,-nodal, -lymphatic or intra-venous administration Peptide lyophilization, testing Adenovirus production (not fully GMP, with Vector Core) Assay standardization, normal control ranges Mixed lymphocyte-tumor cultures Cytotoxicity ( 51 Cr-release, FLOCA, CD107a). Proliferation ( 3 H-thymidine and CFSE) Multiparameter flow cytometry (effectors, regulatory (Treg, MDSC) cells) Single-cell T-cell assays (ELISPOT, CFC, and tetramer) Signaling molecules Frequency of apoptotic T cells Anti-tumor antibodies Cytokine/chemokine analysis (Luminex, ELISA) Data entry and analysis

24 Standard Operating Procedures (SOPs) UNIVERSITY OF PITTSBURGH CANCER INSTITUTE IMMUNOLOGIC MONITORING AND CELLULAR PRODUCTS LABORATORY PROCEDURE FOR VIRUS INFECTIVITY NEUTRALIZATION ASSAY Purpose and Scope The purpose of this procedure is to test serum for the presence of antibodies to adenovirus which are capable of neutralizing viral infectivity. The assay tests decreasing dilutions of serum for the ability to reduce the efficiency by which an easily transduced cell line (A549) can be transduced with adenovirus encoding egfp (AdVeGFP). The virus makes A549 cells GFP-positive, which is detected by flow cytometry. Serum samples with high levels of neutralizing antibodies will be able to reduce AdveGFP transduction of A549 cells, even after many serial dilutions. This procedure is designed to quantitatively measure the inhibition of adenoviral transduction by serotype-specific neutralizing antibodies that are present in the patient serum. The serum dilutions for this assay are 1:4, 1:8, 1:16, 1:32, 1:64, 1:128, 1:256 and 1:512 in addition to a negative control (A549 cells + medium) and a positive control (A549 cells + virus + medium).

25 Immune Response Correlates with Overall Survival Multiple melanoma antigen peptide vaccine GM-CSF IFN 2b The Kaplan-Meier plot for OS by immune response status is shown for E1696 (Phase II). There was a significant difference in OS by immune response status. Immune responders lived longer than the non-immune responders (median OS 21.3 versus 10.8 months, p=0.033). (Kirkwood, J.M., Clin. Cancer Res. 2009) eastern cooperative oncology group

26 Immune Response: E1696 Melanoma antigen peptide-specific CD8+ T cells MHC Tetramer Analysis: The frequency of vaccine peptide-specific CD8+ T cells was measured by MHC tetramers, showing significant increases for all 3 melanoma antigen peptides (not Flu). %MART-1 CD8+ cells:.29%.36%.39%.53%.53%.43% %effector cells: 10% 16% 18% 17% 17% 16% (p=0.048) (p = ns) The MART-1 and gp100- specific cells differentiated towards effector cells with vaccination. eastern cooperative Schaefer, oncology Int. group J. Cancer, 2011

27 AdVTMM2/DC +/- IFNα trial pt. #1 DC Vaccine Vaccine Phenotype: CPL# HLA DR+ CD86+ CD80+ CD83+ CCR7+ CD40+ CD11c+ CPL % 95% 93% 88% 28% 95% 96% CPL# SAMPLE Intracellular: MART 1 TYROSINASE MAGE A6 CPL mdc (control) prematadvtmm2/dc (vaccine) 6%+ 18%+ 10%+ IL-12p70/IL-10 production by vaccine: IL-12p70 HD DC Pt. mdc Pt. AdV/DC vaccine IL-10 HD DC Pt. mdc Pt. AdV/DC vaccine DC only DC+CD40L DC+LPS DC+CD40L+LPS Immature DC, matdc, premat/adv/dc (vaccine): frozen for mrna per SOP

28 DC Vaccine IL-12p70 Production and Clinical Outcome IL-12p70 production levels positively correlated with time to progression. P.0255 is based on Cox regression followed by likelihoodratio test. Circles indicate patients who have already experienced disease progression; diamonds represent patients who have not experienced recurrence to date (Okada, H. JCO 2010). Assay standardization (Butterfield, JIT 2008).

29 Anti-CTLA-4, Anti-PD-1/PD-L1 Absolute lymphocyte count (ALC) >1,000, increased ALC Serum LDH, CRP, IL-17 Treg MDSC NY-ESO-1 cellular and humoral response Tumor IDO Tumor TIL Tumor PD-L1 Ki67/EOMES in CD4+/CD8+ T cells Exhausted T cells (PD-1/TIM3/LAG-3) Ascierto, Kalos, Schaer, Callahan & Wolchok CCR 2013

30 In Vivo Cross-Presentation How should this be assessed? T cells infiltrating the tumor (antigen source)? Inflammed tumor (mrna/protein)? Broad antigen recognition (many CD8+ T cell clones activated)? Functional cellular + humoral immunity induced? Tumor private/mutated antigen responses? Reduced immune suppression? suppression tumor effectors

31 Recommendations: Variability: 1. Patient 2. Blood draw 3. Processing/cryo/thaw 4. Cellular product 5. Assay choice 6. Assay conduct 7. Assay analysis 8. Data reporting 9. Next cool new assay Recommendations: 1. Save DNA/RNA/cells/tumor; include healthy donor control 2. Standardized procedures 3. Standardized procedures 4. Functional assays to characterize/develop potency 5. Standardized, functional 6. SOP 7. Appropriate biostatistical methods 8. Full details, controls, QA 9. Sufficient blood/tissue to interrogate the samples now, as well as later, to generate new hypotheses. tumor DC

32 Acknowledgements SITC Immunotherapy Biomarkers Taskforce UPCI/Butterfield Lab Lazar Vujanovic, Ph.D., Angela Pardee, Ph.D. Jian Shi, M.D., Hadas Prag Naveh, M.D. Univ. Pittsburgh Center for Biological Imaging (S. Watkins),Vector Core (A. Gambotto), Immunologic Monitoring and Cellular Products Lab University of Pittsburgh Cancer Institute NIH RO1 CA104524, NIH RO1 CA NIH 1P50 CA (Kirkwood, J.M., PI, Skin SPORE) The Pittsburgh Foundation The Hillman Foundation